{"title":"Technique of Real-Time Detection of Technical Surface Defects","authors":"L. V. Markova","doi":"10.3103/S1068366623060089","DOIUrl":null,"url":null,"abstract":"<p>A technique and an algorithm of digital surface image processing are proposed to increase the validity of real-time detection of small size defects. The algorithm is implemented in the MATLAB programming environment. The technique is based on segmentation of the high-frequency component of surface texture because small size defects are especially pronounced in this component. The high-frequency component, in particular roughness, is extracted by means of wavelet transform for frequency components separation and homomorphic filtration for compensation of low-frequency distortion caused by nonuniform illumination of test surface. Segmentation of the high-frequency texture component consists in formation of a binary image using the texture descriptors derived from the gray-level co-occurrence matrix as the segmentation threshold. The proposed technique and algorithm are approved in applications to defect detection for a simulated surface, for real ground surface of hardened steel, and for surfaces of carbon fiber reinforced plastic composite. Extraction efficiency of the high-frequency component of surface texture is shown. It is found that texture descriptors, “contrast’ and “energy,” can be applied as segmentation thresholds for defect extraction/determination on the ground (anisotropic) surface while segmentation of an image of a plastic composite (isotropic) surface is effective just with “energy” as a threshold. The proposed technique can be applied for simultaneously real-time monitoring the surface texture and detecting the small size defect in machine vision systems during production and operation of tribosystems.</p>","PeriodicalId":633,"journal":{"name":"Journal of Friction and Wear","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Friction and Wear","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.3103/S1068366623060089","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
A technique and an algorithm of digital surface image processing are proposed to increase the validity of real-time detection of small size defects. The algorithm is implemented in the MATLAB programming environment. The technique is based on segmentation of the high-frequency component of surface texture because small size defects are especially pronounced in this component. The high-frequency component, in particular roughness, is extracted by means of wavelet transform for frequency components separation and homomorphic filtration for compensation of low-frequency distortion caused by nonuniform illumination of test surface. Segmentation of the high-frequency texture component consists in formation of a binary image using the texture descriptors derived from the gray-level co-occurrence matrix as the segmentation threshold. The proposed technique and algorithm are approved in applications to defect detection for a simulated surface, for real ground surface of hardened steel, and for surfaces of carbon fiber reinforced plastic composite. Extraction efficiency of the high-frequency component of surface texture is shown. It is found that texture descriptors, “contrast’ and “energy,” can be applied as segmentation thresholds for defect extraction/determination on the ground (anisotropic) surface while segmentation of an image of a plastic composite (isotropic) surface is effective just with “energy” as a threshold. The proposed technique can be applied for simultaneously real-time monitoring the surface texture and detecting the small size defect in machine vision systems during production and operation of tribosystems.
期刊介绍:
Journal of Friction and Wear is intended to bring together researchers and practitioners working in tribology. It provides novel information on science, practice, and technology of lubrication, wear prevention, and friction control. Papers cover tribological problems of physics, chemistry, materials science, and mechanical engineering, discussing issues from a fundamental or technological point of view.